It's like this with a lot of things now. For example, Nix's learning curve used to be a huge barrier to entry. Now with LLMs, I'm using nix-darwin and home-manager for dotfiles, package management, and have individual flakes in all of my projects for cryptographically reproducible builds!
Nit: there’s nothing “cryptographic” about reproducible builds. “Reproducible build” already usually implies bit-by-bit reproducibility.
i thought it mainly implied architectural/hardware compatibility and deterministic output
Yeah, CAD has been my personal example of "oh the barrier to entry for this skill was high enough that I didn't do it and now I can be passably bad at it enough to get some simple things done" I've had similar experiences with making simple functional parts off a 3d printer with OpenSCAD + LLMs. I'm very aware that the models are worse at it than say, generating react code, and I'm also the antithesis of a skilled pi…
It's like this with a lot of things now. For example, Nix's learning curve used to be a huge barrier to entry. Now with LLMs, I'm using nix-darwin and home-manager for dotfiles, package management, and have individual flakes in all of my projects for cryptographically reproducible builds!
Nix is also great at work. You keep the server nix code in the same repo and OpenCode can just change and test server config.
I'm unconvinced, this is one of the most iconic historical buildings with tomes written about it and plenty of existing photographs and public models to train on.
I would be more interested in benchmarking the modeling of an anonymous structure based on provided references alone. It kind of feels like the shallow magic of watching an LLM one-shot a to-do app..
Last weekend I bought my wife a bike off marketplace. It was in good condition but was missing one of the internal cable routing grommets. I gave Claude pictures of the pill-shaped hole by itself and with my digital calipers in the long and short directions. Gave it a short prompt and it gave me an openscad model with everything parametrized. I printed with no changes in tpu and it was nearly perfect on the first try…
I was recently trying to get models to generate a 3D fortune cookie. Claude in three.js and Gemini in openSCAD. Neither really got the concept or could get very close at all. It's a surprisingly complex shape I guess.
with the shape you probably want something thats good at bends/fabric
cause youd start with the flat shape, the set some contraints that certain edges are colinear
It's like this with a lot of things now. For example, Nix's learning curve used to be a huge barrier to entry. Now with LLMs, I'm using nix-darwin and home-manager for dotfiles, package management, and have individual flakes in all of my projects for cryptographically reproducible builds!
Nit: there’s nothing “cryptographic” about reproducible builds. “Reproducible build” already usually implies bit-by-bit reproducibility.
I meant with Nix you're comparing hashes. With Docker, you're using pinned versions
To be brutally honest, I'm disappointed with antiGravity. It feels incredibly unGoogle-like. The AI billing models are fragmented, and the AntiGravity IDE is currently tripping over something as trivial as a basic Electron deployment config bug. Don't get me wrong, I don't think AI coding is a bad thing. For East Asians like myself, it levels the playing field with Westerners, so as long as you rigorously review the…
> For East Asians like myself, it levels the playing field with Westerners Why do you say that? Are there language or cultural disadvantages to being East Asian?
It’s less about overt disadvantages and more about the practical linguistic and cultural friction we face when reading documentation or engaging with the community. For instance, the open-source ecosystem is deeply rooted in US-centric culture, heavily relying on Western idioms, jokes, and implicit cultural context in discussions. I wouldn't call this 'disadvantages,' but it certainly acts as a handicap and adds an extra layer of cognitive load to our learning curve
Antigravity may well Top the whatever benchmark but: My Antigravity (forced) replacement for Gemini CLI requires me to log on via browser every time I use it, and my Antigravity IDE won't update at all, so: If it's ok I'd prefer they just work on reaching a baseline acceptable rollout before worrying about being Top in anything. Ps actual title: OpenSCAD LLM Benchmark: Building the Pantheon
I've got an AI pro plan and haven't been able to log in for months. Endless checking in with my google support guy. At least Dinesh wishes me good health every week, so that's nice.
Isn't CadQuery more professionally than OpenSCAD close to traditional CAD / mechanical engineering workflows. Not sure which model (ChatGPT, Gemini, and Claude Code) is better for CadQuery code generation?
I tried Claude code designing a snap fit, vase mode printed box. Ultimately didn't work out, it couldn't get the tolerances right and kept designing features that wouldn't print in vase mode. Scad needs unit tests. It would be powerful to asset that a profile doesn't have slope greater than 45°, that intersection of two objects is null, or specific volume. It also needs cut away views. I got okay results using boxes…
"Vase mode snap-fit box" sounds to me like "flexible concrete".